Final Year Project 2009: Lego Robots Guided By WiFi Devices Back
- Advisor: Prof. Qiang Yang
- Teaching Assistant: Derek Hao Hu
- FYP Students: Nick (cs_jwt), King (cs_ckyaf); Ash(cs_lckam), Rex(cs_shw)
- NEW: Please check
here for examples of FYP progress reports from previous groups.
Objective and Requirements
- In this project, our aim is to develop applications that can guide the movement or the actions of Lego robots through
WiFi localization devices.
- The program should run in a client-server mode where the Lego robot acts as a client and receives command from the computer.
Meanwhile, it also collects WiFi signal strength data and sends them back to the computer / PDA.
Reader's Guide
- Here I provide some technical documents as well as papers for you to read. Most technical documents describe how you
can establish connections with laptop computer and Lego, or Lego and PDA. There are also tutorials about how to program
using some publicly available SDKs on Lego.
- I also provide some papers related to localization (location estimation). Papers marked as
(Recommended) are recommended by me and you should read them first.
Lego NXT Related
Localization
- P. Bahl and V. N. Padmanabhan.
RADAR: An In-building RF-based User Location and Tracking
System. In Proceedings of IEEE INFOCOM2000, pp. 775-784, 2000. (Recommended)
- M. Youssef, A. Agrawala and U. Shankar.
WLAN Location Determination via Clustering and
Probability Distributions. In Proceedings of IEEE PerCom2003, March 2003. (Recommended)
- T. Roos, et al. A Probabilistic Approach to WLAN User Location Estimation. International
Journal of Wireless Information Networks, vol. 9, no. 3, pp. 155-164, July 2002.
- Jeffrey J. Pan, Qiang Yang, Hong Chang and Dit-Yan Yeung.
A Manifold Regularization Approach to Calibration Reduction for Sensor-Network Based Tracking. In Proceedings of the Twenty-First
National Conference on Artificial Intelligence (AAAI-06). (Recommended)
- Xiaoyong Chai and Qiang Yang.
Reducing the Calibration Effort for Location Estimation Using Unlabeled Samples.
In Proceedings of the 3rd Annual IEEE International Conference on Pervasive
Computing and Communications, 2005. (Recommended)
- Vincent W. Zheng, Evan W. Xiang, Qiang Yang and Dou Shen.
Transferring Localization Models Over Time.
In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-08). Chicago, Illinois, USA. July 2008.
- Vincent W. Zheng, Sinno J. Pan, Qiang Yang and Jeffrey J. Pan.
Transferring
Multi-device Localization Models using Latent Multi-task Learning. In
Proceedings of the 23rd AAAI Conference on Artificial Intelligence
(AAAI-08). Chicago, Illinois, USA. July 2008.
- Sinno J. Pan, Dou Shen, Qiang Yang and James T. Kwok.
Transferring Localization Models Across Space. In Proceedings of the
23rd AAAI Conference on Artificial Intelligence (AAAI-08). Chicago,
Illinois, USA. July 2008.
- Qiang Yang, Sinno J. Pan and Vincent W. Zheng.
Estimating Location
Using Wi-Fi. In IEEE Intelligent Systems. Volume 23, No.1, Pages 8-13,
Jan/Feb, 2008.
- Jeffrey J. Pan, Qiang Yang and Jialin Pan.
Online Co-Localization in Indoor Wireless Networks by Dimension Reduction.
In Proceedings of the 22nd National Conference on Artificial Intelligence
(AAAI-07) July, 2007.
- Sinno J. Pan, James T. Kwok, Qiang Yang and Jeffrey J. Pan.
Adaptive Localization in a Dynamic WiFi Environment Through Multi-view
Learning. In Proceedings of the 22nd National Conference on Artificial
Intelligence (AAAI-07) July, 2007.
- Jeffrey J. Pan and Qiang Yang.
Co-Localization from Labeled and Unlabeled Data Using Graph Laplacian.
In Proceedings of the Twentieth International Joint Conference on Artificial
Intelligence (IJCAI-07). Hyderabad,India. Jan, 2007.
- Jeffrey J. Pan, James T. Kwok, Qiang Yang and Yiqiang Chen.
Accurate and low-cost location estimation using kernels. In Proceedings
of the Nineteenth International Joint Conference on Artificial Intelligence
(IJCAI-05), July 2005.